SDG8-Mediated Histone Methylation and RNA Processing Function in the Response to Nitrate Signaling.

Chromatin modification has gained increased attention for its role in the regulation of plant responses to environmental changes, but the specific mechanisms and molecular players remain elusive. Here, we show that the Arabidopsis (Arabidopsis thaliana) histone methyltransferase SET DOMAIN GROUP8 (SDG8) mediates genome-wide changes in H3K36 methylation at specific genomic loci functionally relevant to nitrate treatments. Moreover, we show that the specific H3K36 methyltransferase encoded by SDG8 is required for canonical RNA processing, and that RNA isoform switching is more prominent in the sdg8-5 deletion mutant than in the wild type. To demonstrate that SDG8-mediated regulation of RNA isoform expression is functionally relevant, we examined a putative regulatory gene, CONSTANS, CO-like, and TOC1 101 (CCT101), whose nitrogen-responsive isoform-specific RNA expression is mediated by SDG8. We show by functional expression in shoot cells that the different RNA isoforms of CCT101 encode distinct regulatory proteins with different effects on genome-wide transcription. We conclude that SDG8 is involved in plant responses to environmental nitrogen supply, affecting multiple gene regulatory processes including genome-wide histone modification, transcriptional regulation, and RNA processing, and thereby mediating developmental and metabolic processes related to nitrogen use.

Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO3- uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine.

Differential dynamics of the mammalian mRNA and protein expression response to misfolding stress.

The relative importance of regulation at the mRNA versus protein level is subject to ongoing debate. To address this question in a dynamic system, we mapped proteomic and transcriptomic changes in mammalian cells responding to stress induced by dithiothreitol over 30 h. Specifically, we estimated the kinetic parameters for the synthesis and degradation of RNA and proteins, and deconvoluted the response patterns into common and unique to each regulatory level using a new statistical tool. Overall, the two regulatory levels were equally important, but differed in their impact on molecule concentrations. Both mRNA and protein changes peaked between two and eight hours, but mRNA expression fold changes were much smaller than those of the proteins. mRNA concentrations shifted in a transient, pulse-like pattern and returned to values close to pre-treatment levels by the end of the experiment. In contrast, protein concentrations switched only once and established a new steady state, consistent with the dominant role of protein regulation during misfolding stress. Finally, we generated hypotheses on specific regulatory modes for some genes.

An 18S rRNA Workflow for Characterizing Protists in Sewage, with a Focus on Zoonotic Trichomonads.

Microbial eukaryotes (protists) are important components of terrestrial and aquatic environments, as well as animal and human microbiomes. Their relationships with metazoa range from mutualistic to parasitic and zoonotic (i.e., transmissible between humans and animals). Despite their ecological importance, our knowledge of protists in urban environments lags behind that of bacteria, largely due to a lack of experimentally validated high-throughput protocols that produce accurate estimates of protist diversity while minimizing non-protist DNA representation. We optimized protocols for detecting zoonotic protists in raw sewage samples, with a focus on trichomonad taxa. First, we investigated the utility of two commonly used variable regions of the 18S rRNA marker gene, V4 and V9, by amplifying and Sanger sequencing 23 different eukaryotic species, including 16 protist species such as Cryptosporidium parvum, Giardia intestinalis, Toxoplasma gondii, and species of trichomonad. Next, we optimized wet-lab methods for sample processing and Illumina sequencing of both regions from raw sewage collected from a private apartment building in New York City. Our results show that both regions are effective at identifying several zoonotic protists that may be present in sewage. A combination of small extractions (1 mL volumes) performed on the same day as sample collection, and the incorporation of a vertebrate blocking primer, is ideal to detect protist taxa of interest and combat the effects of metazoan DNA. We expect that the robust, standardized methods presented in our workflow will be applicable to investigations of protists in other environmental samples, and will help facilitate large-scale investigations of protistan diversity.

Genomic Methods and Microbiological Technologies for Profiling Novel and Extreme Environments for the Extreme Microbiome Project (XMP).

The Extreme Microbiome Project (XMP) is a project launched by the Association of Biomolecular Resource Facilities Metagenomics Research Group (ABRF MGRG) that focuses on whole genome shotgun sequencing of extreme and unique environments using a wide variety of biomolecular techniques. The goals are multifaceted, including development and refinement of new techniques for the following: 1) the detection and characterization of novel microbes, 2) the evaluation of nucleic acid techniques for extremophilic samples, and 3) the identification and implementation of the appropriate bioinformatics pipelines. Here, we highlight the different ongoing projects that we have been working on, as well as details on the various methods we use to characterize the microbiome and metagenome of these complex samples. In particular, we present data of a novel multienzyme extraction protocol that we developed, called Polyzyme or MetaPolyZyme. Presently, the XMP is characterizing sample sites around the world with the intent of discovering new species, genes, and gene clusters. Once a project site is complete, the resulting data will be publically available. Sites include Lake Hillier in Western Australia, the "Door to Hell" crater in Turkmenistan, deep ocean brine lakes of the Gulf of Mexico, deep ocean sediments from Greenland, permafrost tunnels in Alaska, ancient microbial biofilms from Antarctica, Blue Lagoon Iceland, Ethiopian toxic hot springs, and the acidic hypersaline ponds in Western Australia.